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Sample functions, i.e., stochastic process realizations, are used to define cumulative damage phenomena which end into an observable terminal state or failure. The complexity inherent to such phenomena justifies the use of phenomenological models associated with the evolution of a physical magnitude feasible to be monitored during the test. Sample functions representing the damage evolution may be identified, once normalized to the interval [0,1], with cumulative distribution functions (cdfs), generally, of the generalized extreme value (GEV) family. Though usually only a fraction of the whole damage evolution, according to the specific problem handled, is available from the test record, the phenomenological models proposed allow the whole damage process to be recovered. In this way, down- and upwards extrapolations of the whole damage process beyond the scope of the experimental program are provided as a fundamental tool for failure prediction in the practical design. The proposed methodology is detailed and its utility and generality confirmed by its successive application to representative well-known problems in fatigue and fracture characterization. The excellent fittings, the physical interpretation of the model parameters and the good expectations to achieve a complete probabilistic analysis of these phenomena justify the interest of the proposed phenomenological approach with possible applications to other cumulative damage processes.
The aim of this study is to develop polymeric thin films for corrosion protection of magnesium alloy AZ31. As polymer matrix, poly(4-vinyl pyridine) (P4VP) is selected due to its semiconducting properties and protonic conductivity. Polyacrylic acid is tested as crosslinking layers to improve interfacial adhesion. The macroscopic corrosion properties of the multilayer coatings are investigated by means of electrochemical methods, such as linear sweep voltammetry and electrochemical impedance spectroscopy (EIS), in corrosive media simulating technical and biomedical applications. It is demonstrated that thin multilayer coatings can suppress the corrosion rates of magnesium alloys. To our best knowledge, this is the first demonstration of the use of P4VP as a conducting polymer film with protonic conductivity for corrosion protection of magnesium alloys.
The space heating system accounts for 20%~50% of building energy consumption, and may lead to energy waste due to unreasonable controls. In this study, an energy-efficient floor heating system with intelligent control was proposed to improve energy efficiency of the system. In order to validate the concept of the proposed intelligent control, an experimental system was designed and constructed in Chengdu, China. Temperature, control cycle and energy consumption were then studied under different control strategies. The result shows that a larger flow rate of supply water will result in a longer control cycle and a lower control frequency, i.e., the average control cycle at 7 L min−1 is 1.7 h during the test day, while it is 1.5 h at 5 L min−1. Moreover, adopting water with a higher temperature and flow rate could achieve a higher efficiency of the system. The energy consumptions in case 1 (5 L min−1, 50 °C), case 2 (5 L min−1, 55 °C), case 5 (7 L min−1, 55 °C) and case 6 (7 L min−1, 60 °C) are 4746 kJ, 3534 kJ, 3093 kJ and 3028 kJ, respectively. Based on the experimental data, the supply water temperature is suggested to set lower than 60 °C considering human comfort.
The microscopic diffusion and the low frequency density of states (VDOS) of PIM-EATB(CH3) are investigated by inelastic and quasi-elastic neutron scattering where also the demethylated counterpart of PIM-EA-TB(H2) is considered. These intrinsic microporous polymers are characterized by large BET surface area values of several hundred m2/g and pore sizes between 0.5 and 2 nm. Detailed comparison is made to the archetype of polymers of intrinsic microporosity, PIM-1, and polynorbornenes also bearing a microporosity. Due to the wavelength of neutrons, the diffusion and vibrations can be addressed on microscopic length and time scales. From the inelastic neutron scattering experiments the low frequency density of states (VDOS) is estimated which shows excess contributions to the Debye-type VDOS known as Boson peak. It was found that the maximum frequency of the Boson peak decreases with increasing microporosity characterized by the BET surface area. However, besides the BET surface area, additional factors such as the backbone stiffness govern the maximum frequency of the Boson peak. Further the mean squared displacement related to microscopic motions was estimated from elastic fixed window scans. At temperatures above 175 K, the mean squared displacement PIM-EA-TB(CH3) is higher than that for the demethylated counterpart PIM-EA-TB(H2). The additional contribution found for PIM-EATB(CH3) is ascribed to the rotation of the methyl group in this polymer because the only difference between the two structures is that PIM-EA-TB(CH3) has methyl groups where PIM-EA-TB(H2) has none. A detailed comparison of the molecular dynamics is also made to that of PIM-1 and the microporous polynorbornene PTCNSi1. The manuscript focuses on the importance of vibrations and the localized molecular mobility characterized by the microscopic diffusion on the gas Transport in polymeric separation membranes. In the frame of the random gate model localized fluctuations can open or close bottlenecks between pores to enable the diffusion of gas molecules.
Amorphous, porous materials represent by far the largest proportion of natural and men-made materials. Their pore networks consists of a wide range of pore sizes, including mesoand macropores. Within such a pore network, material moisture plays a crucial role in almost all transport processes. In the hygroscopic range, the pores are partially saturated and liquid water is only located at the pore fringe due to physisorption. Therefore, material parameters such as porosity or median pore diameter are inadequate to predict material moisture and moisture transport. To quantify the spatial distribution of material moisture, Hillerborg’s adsorption Theory is used to predict the water layer thickness for different pore geometries. This is done for all pore sizes, including those in the lower nanometre range. Based on this approach, it is shown that the material moisture is almost completely located in mesopores, although the pore network is highly dominated by macropores. Thus, mesopores are mainly responsible for the moisture storage capacity, while macropores determine the moisture transport capacity, of an amorphous material. Finally, an electrical analogical circuit is used as a model to predict the diffusion coefficient based on the pore-size distribution, including physisorption.
Biocides used as disinfectants are important to prevent the transmission of pathogens, especially during the current antibiotic resistance crisis. This crisis is exacerbated by phenotypically tolerant persister subpopulations that can survive transient antibiotic Treatment and facilitate resistance evolution. Here, we show that E. coli displays persistence against a widely used disinfectant, benzalkonium chloride (BAC). Periodic, persister-mediated failure of disinfection rapidly selects for BAC tolerance, which is associated with reduced cell Surface charge and mutations in the lpxM locus, encoding an enzyme for lipid A biosynthesis.
Moreover, the fitness cost incurred by BAC tolerance turns into a fitness benefit in the presence of antibiotics, suggesting a selective advantage of BAC-tolerant mutants in antibiotic environments. Our findings highlight the links between persistence to disinfectants and resistance evolution to antimicrobials.
Lignosulfonates are industrial biorefinery products that are characterized by significant variability and heterogeneity in their structural composition. Typically, they exhibit high dispersities in molar mass (molar mass distribution-MMD) and in functionalities (functionality-type distribution - FTD), which crucially affect their material usage. In terms of FTD, state-of-the-art Lignin analytics still rely mainly on the determination of functional group contents, which are statistical averages with limited explanatory power. In contrast, our online hydrophobic interaction chromatography−size-exclusion chromatography 2D-LC approach combines the determination of both MMD and FTD in a single measurement to provide a comprehensive picture of the characteristic composition of industrial lignosulfonates information hitherto inaccessible by state-of-the-art lignin analytics. In this way, the complex inter - relationships between these two important structural parameters can be studied in an unprecedented manner. In this study, we reveal the considerable differences in terms of hydrophobic composition and its dispersity present in a range of different industrial lignosulfonates - data desperately needed in tailoring and refining of lignosulfonate composition for material usage.
Spherical lignin nanoparticles (LNPs) fabricated via nanoprecipitation of dissolved lignin are among the most attractive biomass-derived nanomaterials. Despite various studies exploring the methods to improve the uniformity of LNPs or seeking more application opportunities for LNPs, little attention has been given to the fundamental aspects of the solvent effects on the intrinsic properties of LNPs. In this study, we employed a variety of experimental techniques and molecular dynamics (MD) simulations to investigate the solvent effects on the intrinsic properties of LNPs. The LNPs were prepared from softwood Kraft lignin (SKL) using the binary solvents of aqueous acetone or aqueous tetrahydrofuran (THF) via nanoprecipitation. The internal morphology, porosity, and mechanical properties of the LNPs were analyzed with electron tomography (ET), small-angle X-ray scattering (SAXS), atomic force microscopy (AFM), and intermodulation AFM (ImAFM). We found that aqueous acetone resulted in smaller LNPs with higher uniformity compared to aqueous THF, mainly ascribing to stronger solvent−lignin interactions as suggested by MD simulation results and confirmed with aqueous 1,4-dioxane (DXN) and aqueous dimethyl sulfoxide (DMSO).
More importantly, we report that both LNPs were compact particles with relatively homogeneous density distribution and very low porosity in the internal structure. The stiffness of the particles was independent of the size, and the Young’s modulus was in the range of 0.3−4 GPa. Overall, the fundamental understandings of LNPs gained in this study are essential for the design of LNPs with optimal performance in applications.
Resistance spot welding is an established joining process for the production of safetyrelevant components in the automotive industry. Therefore, consecutive process monitoring is essential to meet the high quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals, to ensure individual spot weld quality. The predictive accuracy of such algorithms depends on the provided training data set, and the prediction of untrained data is challenging. The aim of this paper was to investigate the extrapolation capability of a multi-layer perceptron model. That means, the predictive performance of the model was tested with data that clearly differed from the training data in terms of material and coating composition. Therefore, three multi-layer perceptron regression models were implemented to predict the nugget diameter from process data. The three models were able to predict the training datasets very well. The models, which were provided with features from the dynamic resistance curve predicted the new dataset better than the model with only process parameters. This study shows the beneficial influence of process signals on the predictive accuracy and robustness of artificial neural network algorithms.
Especially, when predicting a data set from outside of the training space.
In this paper, the accurate determination of the size and size distribution of bipyramidal anatase nanoparticles (NPs) after deposition as single particles on a silicon substrate by correlative Scanning Electron Microscopy (SEM) with Atomic Force Microscopy (AFM) analysis is described as a new measurement procedure for metrological purposes. The knowledge of the exact orientation of the NPs is a crucial step in extracting the real 3D dimensions of the particles. Two approaches are proposed to determine the geometrical orientation of individual nano‐bipyramides: (i) AFM profiling along the long bipyramid axis and (ii) stage tilting followed by SEM imaging. Furthermore, a recently developed method, Transmission Kikuchi Diffraction (TKD), which needs preparation of the crystalline NPs on electron‐transparent substrates such as TEM grids, has been tested with respect to its capability of identifying the geometrical orientation of the individual NPs. With the NPs prepared homogeneously on a TEM grid, the transmission mode in a SEM, i.e., STEM‐in‐SEM (or T‐SEM), can be also applied to extract accurate projection dimensions of the nanoparticles from the same sample area as that analysed by SEM, TKD and possibly AFM. Finally, Small Angle X‐ray Scattering (SAXS) can be used as an ensemble technique able to measure the NPs in liquid suspension and, with ab‐initio knowledge of the NP shape from the descriptive imaging techniques, to provide traceable NP size distribution and particle concentration.
Laser-induced periodic surface structures (LIPSS) are a simple and robust route for the nanostructuring of solids that can create various surface functionalities featuring applications in optics, medicine, tribology, energy technologies, etc. While the current laser technologies already allow surface processing rates at the level of m2/min, industrial applications of LIPSS are sometimes hampered by the complex interplay between the nanoscale surface topography and the specific surface chemistry, as well as by limitations in controlling the processing of LIPSS and in the long-term stability of the created surface functions. This Perspective article aims to identify some open questions about LIPSS, discusses the pending technological limitations, and sketches the current state of theoretical modelling. Hereby, we intend to stimulate further research and developments in the field of LIPSS for overcoming these limitations and for supporting the transfer of the LIPSS technology into industry.
Detection of surface breaking cracks using flying line laser thermography: A Canny-based algorithm
(2021)
In this work, we introduce a new algorithm for effectual crack detection using flying line laser thermography, based on the well-known Canny approach. The algorithm transforms the input thermographic sequence into an edge map. Experimental measurements are performed on a metallic component that contains surface breaking cracks due to industrial use. The specimen is tested using flying line thermography at different scanning speeds and laser input powers. Results obtained with the proposed algorithm are additionally compared with a previously established algorithm for flying spot thermography. The proposed Canny-based algorithm can be used in automated systems for thermographic non-destructive testing.
Reported here is the production of molecularly imprinted polymer (MIP) films, integrating a fluorescent moiety that serves as both an element for template interaction and signalling, for the thermal and optical detection of the beta-lactam antibiotic nafcillin. Fluorescein methacrylate (FluMa) was synthesized and introduced during the molecular imprinting process as the sole monomer and in a 1 : 1 mixture with methacrylic acid (MAA), allowing to draw first conclusions on the MIP formation potential of such a rather large and rigid monomer. At first, MIP microparticles containing FluMa were prepared by free radical polymerisation. Optical batch rebinding experiments revealed that FluMa can act as a functional monomer for selective detection of nafcillin; however, the addition of MAA as co-monomer significantly improved performance. Subsequently, thin MIP films containing FluMa were deposited onto functionalised glass slides and the influence of porogen, drying time, and monomer composition was studied. These MIP-functionalised glass electrodes were mounted into a customised 3D-printed flow cell, where changes in the liquid were either evaluated with a thermal device or using fluorescence bright field microscopy. Thermal analysis demonstrated that multiple MIP layers enhanced sensor specificity, with detection in the environmentally relevant range. The fluorescence bright field microscope investigations validated these results, showing an increase in the fluorescence intensity upon exposure of the MIP-functionalised glass slides to nafcillin solutions. These are promising results for developing a portable sensor device that can be deployed for antibiotics outside of a dedicated laboratory environment, especially if sensor design and fluorophore architecture are optimised.
Rare-earth based luminescent materials are key functional components for the rational design of light-conversion smart devices. Stable Eu3+-doped strontium fluoride (SrF2) nanoparticles were prepared at room temperature in ethylene glycol. Their luminescence depends on the Eu content and changes after heat treatment. The crystallinity of heat-treated material increases in comparison with as-synthesized samples. Particles were investigated in solution using X-ray diffraction, small-angle X-ray scattering, and X-ray spectroscopy. After heat treatment, the size of the disordered nanoparticles increases together with a change of their local structure. Interstitial fluoride ions can be localized near Eu3+ ions. Therefore, non-radiative relaxation from other mechanisms is decreased. Knowledge about the cation distribution is key information for understanding the luminescence properties of any material.
The co-crystallisation of [NiEn3](NO3)2 (En = ethylenediamine) with Na2MoO4 and Na2WO4 from a water solution results in the formation of [NiEn3](MoO4)0.5(WO4)0.5 co-crystals. According to the X-ray diffraction analysis of eight single crystals, the parameters of the hexagonal unit cell (space group P–31c, Z = 2) vary in the following intervals: a = 9.2332(3)–9.2566(6); c = 9.9512(12)–9.9753(7) Å with the Mo/W ratio changing from 0.513(3)/0.487(3) to 0.078(4)/0.895(9). The thermal decomposition of [NiEn3](MoO4)0.5(WO4)0.5 individual crystals obtained by co-crystallisation was performed in He and H2 atmospheres. The ex situ X-ray study of thermal decomposition products shows the formation of nanocrystalline refractory alloys and carbide composites containing ternary Ni–Mo–W phases. The formation of carbon–nitride phases at certain stages of heating up to 1000 °C were shown.
One of the most commonly diagnosed cancers in men is prostate cancer (PCa). Understanding tumor progression can help diagnose and treat the disease at an early stage. Components of the extracellular matrix (ECM) play a key role in the development and progression of PCa. Elastin is an essential component of the ECM and constantly changes during tumor development. This article visualizes and quantifies elastin in magnetic resonance imaging (MRI) using a small molecule probe. Results were correlated with histological examinations. Using an elastin-specific molecular probe, we were able to make predictions about the cellular structure in relation to elastin and thus draw conclusions about the size of the tumor, with smaller tumors having a higher elastin content than larger tumors.
Human prostate cancer (PCa) is a type of malignancy and one of the most frequently diagnosed cancers in men. Elastin is an important component of the extracellular matrix and is involved in the structure and organization of prostate tissue. The present study examined prostate cancer in a xenograft mouse model using an elastin-specific molecular probe for magnetic resonance molecular imaging. Two different tumor sizes (500 mm3 and 1000 mm3) were compared and analyzed by MRI in vivo and histologically and analytically ex vivo. The T1-weighted sequence was used in a clinical 3-T scanner to calculate the relative contrast enhancement before and after probe administration. Our results show that the use of an elastin-specific probe enables better discrimination between tumors and surrounding healthy tissue. Furthermore, specific binding of the probe to elastin fibers was confirmed by histological examination and laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS). Smaller tumors showed significantly higher signal intensity (p > 0.001), which correlates with the higher proportion of elastin fibers in the histological evaluation than in larger tumors. A strong correlation was seen between relative enhancement (RE) and Elastica–van Gieson staining (R2 = 0.88). RE was related to inductively coupled plasma–mass spectrometry data for Gd and showed a correlation (R2 = 0.78). Thus, molecular MRI could become a novel quantitative tool for the early evaluation and detection of PCa.
In contrast to other cyclic tin bisphenoxides, polymerizations of glycolide and l-lactide with the spirocyclic tin(IV) bis-1,1′-bisnapthoxide yield linear chains having a 1,1′-bisnapthol end group and no cycles. In the case of l-lactide, LA/Cat ratio and temperature are varied and at 160 °C or below, all polylactides mainly consist of even-numbered chains. A total predominance of even-numbered chains is also found for homopolymerization of glycolide, or the copolymerization of glycolide and l-lactide, when conducted <120 °C.
Linear chains having a bisnaphthol end group are again the main reaction products of ring-expansion polymerizations (REP) of 𝝐-caprolactone, but above 150 °C cycles are also formed.
Through connecting genomic and metabolic information, metaproteomics is an essential approach for understanding how microbiomes function in space and time. The international metaproteomics community is delighted to announce the launch of the Metaproteomics Initiative (www.metaproteomics.org), the goal of which is to promote dissemination of metaproteomics fundamentals, advancements, and applications through collaborative networking in microbiome research. The Initiative aims to be the central information hub and open meeting place where newcomers and experts interact to communicate, standardize, and accelerate experimental and bioinformatic methodologies in this feld. We invite the entire microbiome community to join and discuss potential synergies at the interfaces with other disciplines, and to collectively promote innovative approaches to gain deeper insights into microbiome functions and dynamics.
Increasing contamination of environmental waters with pharmaceuticals represents an emerging threat for the drinking water quality and safety. In this regard, fast and reliable analytical methods are required to allow quick countermeasures in case of contamination. Here, we report the development of a magnetic bead-based immunoassay (MBBA) for the fast and cost-effective determination of the analgesic diclofenac (DCF) in water samples, based on diclofenac-coupled magnetic beads and a robust monoclonal anti-DCF antibody. A novel synthetic strategy for preparation of the beads resulted in an assay that enabled for the determination of diclofenac with a significantly lower limit of detection (400 ng/L) than the respective enzyme-linked immunosorbent assay (ELISA). With shorter incubation times and only one manual washing step required, the assay demands for remarkably shorter time to result (< 45 min) and less equipment than ELISA. Evaluation of assay precision and accuracy with a series of spiked water samples yielded results with low to moderate intra- and inter-assay variations and in good agreement with LC–MS/MS reference analysis. The assay principle can be transferred to other, e.g., microfluidic, formats, as well as applied to other analytes and may replace ELISA as the standard immunochemical method.
The concept of a ‘plastisphere microbial community’ arose from research on aquatic plastic debris, while the effect of plastics on microbial communities in soils remains poorly understood. Therefore, we examined the inhabiting microbial communities of two plastic debris ecosystems with regard to their diversity and composition relative to plastic-free soils from the same area using 16S rRNA amplicon sequencing. Furthermore, we studied the plastic-colonizing potential of bacteria originating from both study sites as a measure of surface adhesion to UV-weathered polyethylene (PE) using high-magnification field emission scanning electron microscopy (FESEM). The high plastic content of the soils was associated with a reduced alpha diversity and a significantly different structure of the microbial communities. The presence of plastic debris in soils did not specifically enrich bacteria known to degrade plastic, as suggested by earlier studies, but rather shifted the microbial community towards highly abundant autotrophic bacteria potentially tolerant to hydrophobic environments and known to be important for biocrust formation. The bacterial inoculates from both sites formed dense biofilms on the surface and in micrometer-scale surface cracks of the UV-weathered PE chips after 100 days of in vitro incubation with visible threadlike EPS structures and cross-connections enabling surface adhesion. High-resolution FESEM imaging further indicates that the microbial colonization catalyzed some of the surface degradation of PE. In essence, this study suggests the concept of a ‘terrestrial plastisphere’ as a diverse consortium of microorganisms including autotrophs and other pioneering species paving the way for those members of the consortium that may eventually break down the plastic compounds.